4 accepted papers
Machine unlearning has emerged as an inevitable AI mechanism to support GDPR requirements such as revoking user consent through the "right to be forgotten". However, existing approaches often leave residual traces that make them vulnerable to data reconstruction attacks. In this work, we propose R…
Indoor radio maps with frequency domain data are difficult to reconstruct when only limited measurements at a few locations are available. Naive convolutional neural networks suffer from flawed structures in the frequency domain when predicting these radio maps, resulting in overly smoothed predicti…
Audio-visual parsing (AVP) is a newly emerged multimodal perception task, which detects and classifies audio-visual events in video. However, most existing AVP networks only use a simple attention mechanism to guide audio-visual multimodal events, and are implemented in a single end. This makes it u…
Considering the problem of joint source-channel coding (JSCC) for multi-user transmission of images over noisy channels, an autoencoder-based novel deep joint source-channel coding scheme is proposed in this paper. In the proposed JSCC scheme, the decoder can estimate the signal-to-noise ratio (SNR)…